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A Risk-based Input-Output Methodology for Measuring the Effects of the August 2003 Northeast Blackout


  • Christopher W. Anderson
  • Joost R. Santos
  • Yacov Y. Haimes


The 2003 Northeast Blackout revealed vulnerabilities within the US electric power-grid system. With the economy so dependent on electric power for most aspects of life, a power-grid failure can have far-reaching higher-order effects and can impair the operability of other critical infrastructures. An inoperability of the power sector can result from different types of disasters (e.g., accidents, natural catastrophe, or willful attacks). This paper demonstrates the Inoperability Input-Output Model (IIM) to measure the financial and inoperability effects of the Northeast Blackout. The case study uses information from sources such as the US input-output tables and sector-specific reports to quantify losses for specific inoperability levels. The IIM estimated losses of the same magnitude as other published reports; however, with a detailed accounting of all affected economic sectors. Finally, a risk management framework is proposed to extend the IIM's capability for evaluating investment options in terms of their implementation costs and loss-reduction potentials.

Suggested Citation

  • Christopher W. Anderson & Joost R. Santos & Yacov Y. Haimes, 2007. "A Risk-based Input-Output Methodology for Measuring the Effects of the August 2003 Northeast Blackout," Economic Systems Research, Taylor & Francis Journals, vol. 19(2), pages 183-204.
  • Handle: RePEc:taf:ecsysr:v:19:y:2007:i:2:p:183-204 DOI: 10.1080/09535310701330233

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    References listed on IDEAS

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    7. repec:hhs:iuiwop:430 is not listed on IDEAS
    8. Julda Kielyte, 2008. "Estimating Panel Data Models in the Presence of Endogeneity and Selection," Journal of Economics and Econometrics, Economics and Econometrics Society, vol. 51(2), pages 1-19.
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    Cited by:

    1. Clementina Bruno & Ugo Finardi & Azahara Lorite-Espejo & Elena Ragazzi, 2016. "Emerging costs deriving from blackouts for individual firms: evidence from an Italian case study," quaderni IRCrES 201601, Research Institute on Sustainable Economic Growth - Moncalieri (TO) ITALY - former Institute for Economic Research on Firms and Growth - Moncalieri (TO) ITALY.
    2. Abrate, Graziano & Bruno, Clementina & Erbetta, Fabrizio & Fraquelli, Giovanni & Lorite-Espejo, Azahara, 2016. "A choice experiment on the willingness of households to accept power outages," Utilities Policy, Elsevier, vol. 43(PB), pages 151-164.
    3. repec:eee:reensy:v:94:y:2009:i:4:p:819-829 is not listed on IDEAS
    4. Stéphane Hallegatte, 2012. "Modeling the roles of heterogeneity, substitution, and inventories in the assessment of natural disaster economic costs," Post-Print hal-00802050, HAL.
    5. Chopra, Shauhrat S. & Khanna, Vikas, 2015. "Interconnectedness and interdependencies of critical infrastructures in the US economy: Implications for resilience," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 865-877.
    6. Henriet, Fanny & Hallegatte, Stéphane & Tabourier, Lionel, 2012. "Firm-network characteristics and economic robustness to natural disasters," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 150-167.
    7. repec:eee:reensy:v:121:y:2014:i:c:p:43-60 is not listed on IDEAS
    8. repec:eee:eneeco:v:68:y:2017:i:c:p:177-191 is not listed on IDEAS
    9. Barker, Kash & Santos, Joost R., 2010. "Measuring the efficacy of inventory with a dynamic input-output model," International Journal of Production Economics, Elsevier, vol. 126(1), pages 130-143, July.
    10. Pagani, Giuliano Andrea & Aiello, Marco, 2014. "Power grid complex network evolutions for the smart grid," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 396(C), pages 248-266.
    11. repec:kap:netspa:v:17:y:2017:i:4:d:10.1007_s11067-017-9359-9 is not listed on IDEAS


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